Artificial intelligence (AI)-based models developed by a team of international researchers were able to identify ovarian cancer in ultrasound images more accurately than humans. Results from a study published in Nature Medicine showed that the AI models achieved an accuracy rate of 86.3%, compared to 82.6% for the experts and 77.7% for the non-expert examiners.
Artificial intelligence (AI)-based models developed by a team of international researchers were able to identify ovarian cancer in ultrasound images more accurately than humans. Results from a study published in Nature Medicine showed that the AI models achieved an accuracy rate of 86.3%, compared to 82.6% for the experts and 77.7% for the non-expert examiners.
Artificial intelligence (AI)-based models developed by a team of international researchers were able to identify ovarian cancer in ultrasound images more accurately than humans. Results from a study published in Nature Medicine showed that the AI models achieved an accuracy rate of 86.3%, compared to 82.6% for the experts and 77.7% for the non-expert examiners.
Ovarian cancer diagnostics company, Cleo Diagnostics Ltd. has developed a blood-based diagnostic test for ovarian cancer based on the CXCL10 biomarker, which is produced early and at high levels by ovarian cancers but is largely absent in nonmalignant disease.
